Live microorganisms that provide a health benefit to the host when administered in sufficient quantities are referred to as probiotics (Rao and Samak, 2013). Lactic acid bacteria (LAB) are gaining importance as probiotics because of their beneficial effects in the animal gastrointestinal system (Liew et al., 2005; Pfeiler and Klaenhammer, 2007). Lactobacillus plantarum is a probiotic LAB species that survives in gastric fluid and colonizes the intestinal tract of animals (de Vries et al., 2006). This species produces an antimicrobial substance, plantaricin, which is active against certain pathogens (Ashenafi and Busse, 1991). Considering the advantages of L. plantarum as a probiotic species, many attempts have been made to improve the anti-pathogenic ability of the wild-type strain, such as LP-GS1 (L. plantarum Genome Shuffling mutant 1), which showed a higher inhibitory effect against Escherichia coli K99 than the wild type (Seo, 2012).

With the increasing popularity of probiotics, the related distribution industry is continuously growing. Freeze-drying is a widely used technique for the storage and distribution of probiotics, which is one of the most effective methods for long-term preservation of probiotic quality (Kearney et al., 1990). Freeze-drying is a dehydration method that freezes water inside microbial cells, followed by sublimation to remove the water. Freeze-dried products offer a higher survival rate and are more readily available due to their ease and quickness of dissolution, making them a preferred packaging method compared to others (Selmer-Olsen et al., 1999).

Despite the many advantages of lyophilization, it is a complex process that involves low temperatures, freezing, and drying, all of which can cause stress. These harsh conditions can result in osmotic shock and damage to cell membranes, leading to reduced viability, stability, and metabolic activity of probiotics (Carvalho et al., 2004). As a result, it is essential to optimize freeze-drying methods to ensure the long-term stability of microbial cultures, including viability and functional activity (Li et al., 2010). Suitable cryoprotectants and appropriate drying methods are necessary to achieve ideal lyophilized products (Reddy et al., 2009).

Here, we tested six cryoprotective additives (skim milk, trehalose, monosodium glutamate [MSG], lactose, sucrose, and glycerol) and their combinations to maximize the viability of the probiotic bacterium LP-GS1 during the freeze-drying process and storage. We evaluated the protective effect of cryoprotectants on the microbe by statistical and mathematical techniques, such as Plackett-Burman design (PBD) and central composite design (CCD). These are powerful tools for designing experiments and optimizing different environmental processes. By employing these methods, a reduced number of experiments are required to evaluate multiple parameters (composition of cryoprotectants) and their interactions. This approach allowed rapid and efficient screening of cryoprotective additives to maximize the survival rate of the probiotic lactic acid bacteria.

Materials and strain preparation

All chemicals and materials used in the study were purchased from Sigma-Aldrich, except as specified. Bacterial cultures were prepared using Lysogeny broth (LB), LB agar, De Man, Rogosa and Sharpe agar (MRS) broth, and MacConkey agar from BD Difco. Cryoprotectants were formulated with distilled water as a preparation of a stock solution. Skim milk (BD Difco) and glycerol were sterilized at 110°C for 10 min, while lactose, trehalose, sucrose, and MSG were sterilized using 0.22 μm filter membrane.

For long-term storage, LP-GS1 was stored at -70°C in a glycerol-based freezing medium (15% glycerol salt solution [glycerol 300 ml; Sodium chloride 8.5 g; potassium phosphate dibasic 3 g; potassium phosphate monobasic 1 g; distilled water 700 ml] and 75% MRS culture medium [MRS broth 55 g in 1 L of distilled water]). To prepare the seed culture, a single colony from the MRS agar plate was inoculated in 10 ml MRS broth and cultured overnight at 37°C to increase bacterial activity.

Freeze-drying process and storage

Cultured cells were obtained by centrifuging the solution of the bacterial culture at 4°C, 6000 rpm for 15 min and discarding the supernatant. The cells were then washed three times with 1 × PBS at 4°C, 6000 rpm for 15 min 3 times. Cryoprotectant additives equal to the weight of the cells were mixed (1:1 weight ratio). After pre-freezing, samples were desiccated in a vacuum freeze-dryer at a condenser temperature of -80°C. Dried cells were stored in closed containers in the dark.

Calculation of survival rate

The microbes were suspended in 1 × PBS, and then gradient diluted (within the range of 10^-3 to 10^-5). Subsequently, 100 μl of the suspended microbes was spread uniformly on an MRS plate. The plate was incubated at 37°C for 24 h, and viable bacteria were counted. The survival rate was determined using the following formula:

Where the ‘event’ means freeze-drying, storage, or culture.

Factorial designs for prediction of protection power of cryoprotectants

In order to assess the efficacy of cryoprotectants in protecting microbes during freeze-drying, a Plackett-Burman design (PBD) was employed, which involved 11 factors comprising of 6 variables and 5 virtual variables, assessed across 13 iterations. Each variable was tested at three levels (low level of -1, high level of +1, and intermediate level of 0) along with a center point (Table 1). PBD was based on the first order model as shown below:

Table 1 Plackett-Burman experimental variable range

Symbol	Variables	Experimental value
		-1	0	1
X1	Skim milk	2	8.5	15
X2	Trehalose	2	11	20
X3	Glycerol	2	8.5	15
X4	MSG	1	5.5	10
X5	Sucrose	2	8.5	15
X6	Lactose	2	8.5	15

Where Y is the predicted response, β₀ is the model intercept, β_i is the linear coefficient, and X_i is the variable, and k is the number of variables. The quality of fit of the polynomial model equation was expressed by the coefficient of determination R².

To optimize the freeze-drying process, a Central Composite Design (CCD) with 20 runs and a three-factor and five-level design was used. Each variable (i.e., cryoprotectant) was evaluated at five different concentration levels. Once the experiment was finished, the dependent variable or reaction (Y set) for each experiment was used, and a second-order model was used to fit the response to the independent variables, as shown below:

Where Y is the predicted response (output factors), X_i and X_j are input variables that affect response Y. The number of variables is denoted by k, and the equation includes a constant term β₀, the ith linear coefficient β_i, the first quadratic coefficient β_ii, and the ijth interaction coefficient β_ij (Zhou et al., 2011).

A second-order polynomial equation was used to estimate the biomass concentration based on the experimental results obtained from the CCD:

Where Y is the predicted bacterial survival rate. A, B, and C are the actual percentage of skim milk, trehalose and MSG, respectively.

Statistical analysis

The experiments were conducted in triplicate and the average of the three independent experiments was used. Analysis of variance (ANOVA) was used to determine the significance between the model and the regression coefficient. R² was used to assess the quality of the polynomial equation and Fischer’s F-test was used to test its statistical significance. The interaction between input factors was evaluated using three-dimensional response surface and contour plots predicted by the model. Design-Expert Version 8.0.6.1 (Stat-Ease Inc.) was used for experiment design, regression, and graphical analysis of the experimental data.

Evaluation of six cryoprotective additives

For this study, six materials widely used as probiotic cryoprotectants (skim milk, trehalose, MSG, lactose, sucrose, and glycerol) were selected. In the process of freeze-drying, we first tested three freezing methods before drying with these candidates to ensure the highest survival rate: liquid nitrogen freezing, -70°C freezing, and gradual freezing (for 20 min each, in the sequence of 4 °C, -20°C, and -70°C). The survival rate of LP-GS1 frozen with liquid nitrogen is higher than that of the microbes with both -70°C freezing and gradual freezing regardless of the type of cryoprotective additives (Fig. 1). This result suggests that the relatively rapid freezing method (i.e., liquid nitrogen freezing) confers a higher protective effect on the cells than the other two methods. Glycerol showed a significantly lower protective effect than other cryoprotectant candidates, and there was no significant difference in the survival rate between the other five cryoprotectants in all three freezing methods.

Fig. 1. Protection effect of the cryoprotective additives under different freezing conditions. Liquid nitrogen, Ultra-rapid freezing using liquid nitrogen; -70°C fridge, Rapid freezing at -70°C; Gradual freezing, serial freezing at 4°C, -20°C and -70°C. *p < 0.05.

We then tested the protective effect of individual cryoprotectant candidates at two different environmental temperatures (room temperature [RT] and 4°C) for eight weeks. Skim milk, trehalose, and MSG showed significantly higher protective effects at all time points (4 and 8 weeks) and at all temperatures (RT and 4°C) than glycerol, sucrose, and lactose (Fig. 2A and B). Figure 2C shows that viable cell counts rapidly decreased when stored at room temperature, with less than 10% survival rates after 8 weeks. However, refrigeration preserved the survival rate as ~30% with most of the cryoprotectants (Fig. 2D). These results emphasize the cooperation of the proper types of cryoprotectants and ambient temperature for the long-term storage of probiotic bacteria.

Fig. 2. Effective protection time of the cryoprotectant candidates. (A, B) Survival rate of LP-GS1 with cryoprotectants after freeze-drying and storage for 4 or 8 weeks at RT (A) or 4°C (B). *p < 0.05. (C, D) The number of viable bacterial cell numbers (CFU, colony forming unit) measured every week for 8 weeks at RT (C) or 4°C (D).

Determination of the optimal cryoprotectant combination

The proper combinations of cryoprotective additives provide much more effective protection during the freeze-drying process and distribution of probiotics (Reddy et al., 2009; Khoramnia et al., 2011; Jalali et al., 2012). However, evaluating the composition of cryoprotectants in vitro is a time-consuming and labor-intensive process considering the types of protectants and their compositions. To establish a more efficient way to screen the best combination, we employed mathematical factorial designs to predict the protection effect of cryoprotectant candidates.

Based on the experimental results described above, the PBD was employed to identify significant variables that increase cell viability (Table 2). All values shown in Table 3 indicate that the survival rate of cells is significantly affected by skim milk, trehalose, and MSG, which was consistent with the results shown in Fig. 2. The coefficient of determination (R²) between the experimental values and the predicted results by PBD was 0.9519, indicating that our approach is fitted to predict the protection effects (Pred-R² of 0.7594 and adj-R² of 0.9037). Based on these results, the final candidates for further testing were chosen as skim milk, trehalose, and MSG.

Table 2 Experimental design and results of the Plackett-Burman test

Run	X1	X2	X3	X4	X5	X6	Y1 / survival rate %
1	1	1	-1	1	1	1	91.6915
2	-1	1	1	-1	1	1	67.7532
3	1	-1	1	1	1	-1	75.4374
4	1	1	1	-1	-1	-1	81.7847
5	-1	1	-1	1	1	-1	63.2861
6	0	0	0	0	0	0	72.0158
7	-1	-1	-1	-1	-1	-1	38.4712
8	1	-1	1	1	-1	1	71.6776
9	1	-1	-1	-1	1	-1	53.5812
10	-1	1	1	1	-1	-1	83.4816
11	1	1	-1	-1	-1	1	80.7073
12	-1	-1	-1	1	-1	1	56.0156
13	-1	-1	1	-1	1	1	41.6272

Table 3 Analysis results of PBD to determine significant variables enhancing cell viability.

ANOVA was performed to test statistical significance.

Cryoprotectant	t-value	F value	p-value
Skim milk	5.82	34.63	0.002
Trehalose	7.45	55.43	0.0007
Glycerol	2.11	4.60	0.085
MSG	4.35	19.22	0.0071
Sucrose	1.03	1.12	0.34
Lactose	0.78	0.57	0.48

Next, we determined the optimal ratio of skim milk, trehalose, and MSG for the maximal survival rate of LP-GS1 based on CCD. To employ CCD, the concentration range of each protectant is required (e.g., the maximum concentration not impairing cell viability). The maximal concentrations of skim milk, trehalose, and MSG were experimentally determined as 15%, 20%, and 10%, respectively (Fig. 3A to C). The ranges of concentrations for the three cryoprotectants (skim milk, trehalose, and MSG) were determined based on the results obtained. Skim milk was used in concentrations ranging from 2–15%, trehalose from 2–20%, and MSG from 1–10%. Two second-order polynomial regression models, including the linear model and the quadratic regression model, were obtained by fitting the experimental responses using the least squares method for response surface simplification. The analysis showed that all of the cryoprotectants had significant effects on cell survival (p < 0.0001, R² = 0.9884, Pred-R² = 0.9474, Adj-R² = 0.9779). Figure 3D to F shows the predicted survival rate with each combination of two cryoprotectants. The contour plots (right panels in Fig. 3D to F) corresponding to the three-dimensional figures shaped an ellipse that approximates to a circle, so each protectant had a mutual effect with another cryoprotectant on the survival rate. This result indicates that the balance of the individual concentration should be considered to maximize the survival rate when combining those three cryoprotectants.

Fig. 3. Analysis results of CCD to optimize composition of the cryoprotectants. (A, B, C) Protection effect of different concentration of skim milk (A), trehalose (B) and MSG (C) on LP-GS1. Survival rate (gray circle) and viable cell counts (CFU; black square) of the microbes was measured from the mixture of LP-GS1 and the cryoprotectant (1:1 ratio, w/w). (D, E, F) Three-dimensional response surface plots and two-dimensional contour plots with two cryoprotectants for cell survival rate. Variable interactions of trehalose and skim milk (D), MSG and skim milk (E), and MSG and trehalose (F). (G) Predicted or experimental survival rate of LP-GS1 with the determined composition of the cryoprotectants. The survival rate with 10% skim milk was measured as a control. Statistical test between the predicted value and the experimental value was not able to be applied because the predicted value is single.

The regression equation was analyzed, and the optimal ratio of the three cryoprotective additives was determined as a combination of 5.1% skim milk, 10.55% trehalose, and 4.72% MSG. This composition derived an 82.10% predicted cell survival rate, which was not largely different from the experimental cell survival rate (78.6%; Fig. 3G; the statistical test was not able to be applied due to the single predicted value). The survival rate of the cells with the optimal combination showed a 2.67-fold increase compared to that achieved with 10% skim milk, which is commonly used as a cryoprotective additive in laboratories.

Lactic acid bacteria can be easily affected by the environment and contact with other substances. Freezing them causes the solidification of water, which leads to the production of ice crystals that can damage the cell structure physically and cause cell death (Fahy and Wowk, 2015; Fonseca et al., 2015; Yeo et al., 2018). To mitigate this issue, various cryoprotectants are applied during freeze-drying. This study focused on optimizing the cryoprotectant composition to enhance the cell viability of the L. plantarum strain during lyophilization and storage.

Many factors should be considered when evaluating cryoprotectants, such as the types of cryoprotectants, their concentrations, and their combinations. This work requires a large number of experiments, making it time-consuming and not cost-effective. To overcome these issues, we proposed an efficient way to evaluate cryoprotectants and their combinations by using factorial designs (PBD and CCD). This approach ensured a high survival rate of the probiotic bacterium during freeze-drying and storage, which was consistent with the experimental evaluation. This implies that the process established in this study can be directly applied to the industry to evaluate cryoprotectants and their best combination.

Our study indicated that the proper combination of skim milk, trehalose, and MSG confers superior viability of the lactic acid bacterium LP-GS1 during freeze-drying and storage. Skim milk is widely used as a cryoprotective additive for microorganisms due to its ability to form layers around the cells, providing protection from ice and stabilizing pH by adjusting the level of solutes such as calcium (Carvalho et al., 2004; Ming et al., 2009). Trehalose, a non-reducing disaccharide, confers the ability to survive dehydration and restore activity soon after rehydration (Patist and Zoerb, 2005) by stabilizing and protecting proteins and the cell membrane from dehydration (Elbein et al., 2003). The mechanism of MSG as a cryoprotectant is related to water permeation (Coulibaly et al., 2010), and it stabilizes protein structure by reacting with the amino groups of the microbial proteins, allowing the bacteria to retain greater amounts of residual moisture (de Valdéz et al., 1983). Taken together, the proposed combination of cryoprotectants might provide a stronger protective effect against water transitions that cause imbalances in the intracellular and extracellular electrolyte concentrations.

Several studies have determined optimal formulations of cryoadditives for freeze-drying lactobacilli. All combinations shown in Table 4 include skim milk, which indicates its superiority as a cryoprotectant. Generally, ~10% of sugar-based cryoprotectants (sucrose, lactose, glycerol, and trehalose) were added to the optimal formulations. Interestingly, the composition determined in this study contains a relatively lower concentration of skim milk than the others. It is assumed that MSG helps the cryoprotective effect of skim milk, considering the higher concentration of salt in our formulation than that of the others. MSG is related to oxidative reactions that affect cellular pH (Sharma et al., 2013; Nahok et al., 2019). This suggests that MSG may contribute to stabilizing cellular pH with skim milk. Further studies are needed to fully explain how this combination of cryoprotectants dramatically reduces bacterial cell death, but it is obvious that using proper protective agents is necessary for strong protection during freeze-drying and storage.

Table 4 Comparison of optimal cryoprotectant composition for freeze-drying lactobacilli strains

Species/strain*	Cryoprotectant (%, w/v)						References
	Skim milk	Sucrose	Lactose	Glycerol	Trehalose	Salt
L. plantarum LP-GS1	5.1	-	-	-	10.55	MSG, 4.72	This study
L. acidophilus	21	-	7.50	-	13	Disodium phosphate, 0.33	Shu et al. (2018)
L. brevis ED25	17.28	10	2.12	-	-	-	Gul et al. (2020b)
L. curvatus N19	20	10	3.57	-	-	-	Gul et al. (2020a)
L. rhamnosus GDMCC 1.325	15.7	-	-	9.1	11.1	MSG, 0.35	Chen et al. (2023)
L. plantarum ST-III	25	12.5	-	37.5	12.5	-	Wang et al. (2019)
L. casei LC2W	25	12.5	-	37.5	12.5	-	Wang et al. (2019)
L. bulgaricus	28	-	24	-	-	Sodium ascorbate, 0.48	Chen et al. (2014)
L. salivarius I24	9.85	10.65	-	-	-	-	Ming et al. (2009)
L. salivarius	14	8	-	-	9	-	Ren et al. (2019)
L. agilis	15	8	-	-	7	-	Ren et al. (2019)

*If the strain name is not specified in the literature, only the species name is presented.

동결 건조는 유산균 제품의 안정화를 위해 널리 사용되지만, 이 과정은 미생물 세포를 손상시키므로 공정 중 세포 생존율을 향상시키는 방안이 필요하다. 본 연구에서는 유익균 중 하나인 Lactobacillus plantarum의 동결 건조 과정 중 생존율을 최대화하기 위해 Plackett-Burman design (PBD)과 central composite design (CCD)과 같은 수학적인 factorial design을 사용하여 스크리닝 과정 및 보호제의 종류와 조성을 최적화하였다. 시험관 수준에서의 실험과 PBD에서는 trehalose, skim milk 및 monosodium glutamate (MSG)가 높은 보호 효과를 나타내었으며, 이를 바탕으로 CCD를 활용한 보호제의 최적 조성 예측으로는 skim milk (5.1%), trehalose (10.55%) 및 MSG (4.72%)가 선정되었다. 본 조합을 활용한 L. plantarum의 실제 측정된 생존율은 약 80% 이었으며, 이는 실험실에서 동결보존제로 널리 사용되는 10% skim milk의 보호 효과보다 약 2.67배 높았다. 본 연구를 통해 유산균의 유통을 위해 정밀한 가공이 중요하다는 점을 강조하고자 하며, L. plantarum의 생존율을 최대화하기 위한 적절한 동결보존제 선택 방법을 제안하고자 한다.

This research was supported by Kyungpook National University Research Fund, 2022.

The authors have no conflict of interest to report.